International Journal of Innovation Management Vol. 7, No. 3 (September 2003) pp.1–30 © Imperial College Press

SUCCESS AND FAILURE OF INNOVATION: A LITERATURE REVIEW

GERBEN van der PANNE, CEES van BEERS and ALFRED KLEINKNECHT

Dept. Economics of Innovation, Delft University of Technology The Netherlands

Received 7 January 2003 Revised 16 June 2003

Accepted 17 June 2003 In this paper 43 recent studies on determinants of success and failure of innovation are reviewed. Several studies report a larger number of success factors and provide some rank ordering. Analyzing these ranks, we observe consistency among the studies on the ten highest-ranking success factors; however, the studies are far from consistent when lower-ranking factors are considered. Agreement exists on the positive impact of factors such as firm culture, experience with innovation, multidisciplinary R&D teams or the advantages of the matrix organization. On factors such as fierceness of competition, R&D intensity, top management support and the degree to which a project is innovative or technologically advanced, ambiguity remains. Keywords: Innovation; success factors; viability.

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“But in capitalist reality as distinguished from its textbook picture, it is not…(price) competition which counts but the competition from the new commodity, the new source of supply, the new type of organization…competition which commands a decisive cost or quality advantage and which strikes not at the margins of the profits…of the existing firms but at their very lives. This kind of competition is as much more effective than the other as a bombardment is in comparison with forcing a door.”

(Schumpeter 1943: 84)

Introduction Why does not everybody innovate? It is widely recognized that innovation is key to the economic performance of firms. Innovative firms grow faster in terms of employment and profitability (see for example the econometric studies by Geroski et al., 1993; or Kleinknecht et al., 1997). If nonetheless many firms do not engage in innovation, this is due to several types of uncertainties involved. Asplund and Sandin (1999) and Cozijnsen et al. (2000) observe that only one out of every five projects ever initiated proves viable. Against this background, there is an obvious need to systematically assess factors decisive for success and failure of innovation. Not surprisingly, a large body of literature on success factors has emerged during the past 20 years. At first glance this literature remains inconclusive. Different views exist regarding the relevance of success factors. While some studies argue a certain group of factors being crucial, other studies ignore the very same factors and claim different factors to be decisive. Studies also differ in terms of alleged causalities. This inconsistency among studies may have several reasons. One is the heterogeneity in samples as well as methodology. Samples differ as some studies investigate one specific industry, whereas others cover several industries. Methods differ, as some studies are qualitative while others adopt a quantitative approach. The studies also remain inconsistent in measuring (degrees of) success. There is little effort among the various contributors to assess (causes of) differences between their studies, or as Crawford (1987: 22) puts it: “None tried to compare, except to themselves”. A more general problem is that perceptions may be biased and misleading as respondents are personally involved in the projects evaluated. In this paper it is investigated whether, in spite of a seemingly large diversity, some common insights can be distilled from recent contributions.

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The first major investigation of success factors was the SAPPHO-study (Scientific Activity Predictor from Patterns with Heuristic Origins), conducted in the early 1970s in the United Kingdom. The study compared 29 successful with 29 unsuccessful innovations in chemicals and scientific instruments and found 27 characteristics of the innovation process that discriminated between success and failure. These relate to the innovator’s ability to understand customer needs, marketing capabilities, the efficiency of the development process, the extent to which the firm is able to adequately absorb external information and management skills (Freeman et al., 1972). The SAPPHO-study was followed by Cooper's (1980) study Project NewProd. Based on 200 Canadian innovations, it showed that viability is determined by three factors. Of primary importance is the degree to which the product is unique and superior compared to existing alternatives. The innovator’s understanding of (future) market developments is the second most important factor. Along with the product’s synergy with the firm’s overall technological and manufacturing resources, these factors determine half the product’s viability. Of equal importance is Maidique and Zirger’s (1984) Stanford Innovation Project, arguing that success is the outcome of a wide range of firm and project related factors; a single magical factor does not exist. In addition to these explorative studies, there is a larger literature investigating a wide variety of factors affecting a new product’s viability — technologically as well as commercially. Our review of these studies eventuates in a classification of four major headings (see Figure 1): (1) Firm related factors; (2) Project related factors; (3) Product related factors; and (4) Market related factors. In their assessment of the literature, some authors engaged in meta-analyses, estimating “regressions on regressions” (e.g. Henard & Szymanski, 2001). Given the nature of the literature to be reviewed, we have chosen for a qualitative review as a first step. In order to arrive at a more systematic assessment, we proceed with a rank correlation analysis and round up, in Appendix A, with a stylized overview of all studies reviewed in this paper.

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The qualitative review follows the categories exhibited in Figure 1. In the next section, unambiguous success factors are discussed; factors lacking consensus are reviewed in section 3. In section 4 the rank order analysis is presented. Section 5 covers conclusions. Considering the large number of studies covered, references are confined to those authors typical for (or typically deviant from) a particular argument.

Figure 1:

Critical factors for successful innovation

Technologi-cal viability

Market related factors: • Concentration

of target market • Timing market

introduction • Competition • Marketing

Commercial viability

Success

Product related factors: • Relative price • Relative quality • Innovativeness • Technologically

advanced

Firm related factors: • Firm culture • Experience • R&D team • Strategy towards

innovation • Organisational

structure • R&D intensity

Folsucfirmcom

Project related fac-tors: • Complemen-

tarity • Management

style • Top manage-

ment support

2 Factors of Consensus

lowing the categories exhibited in Figure 1, in this section generally acknowledged cess factors are discussed. Factors affecting the project's technological viability, i.e. and project related factors (Sec. 2.1) are distinguished from determinants of mercial viability, i.e. product and market related factors (Sec. 2.2).

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2.1 Technological viability Firm related factors With respect to the technological viability of an innovation project, four factors concerning the firm are generally considered relevant: the firm's culture, experience with innovation, the Research and Development (R&D) team and the firm’s strategy towards innovation. Firm culture A culture susceptible to innovation is a prerequisite for the firm to acknowledge the necessity to innovate and is therefore undisputedly considered crucial to the firm’s technological capabilities in the long term (e.g. Ekvall & Ryhammar, 1998; Lester, 1998).1 Cultural resistance to innovation may arise from entrenched routines and interpretative barriers. Routines structure activities, processes and information. This tempts employees to focus solely on their own tasks and responsibilities. Consequently, barriers are incurred when searching for solutions that surpass individual responsibilities. This is incompatible with the inherent collective nature of innovation projects, demanding all participants to work towards a common objective (Dougherty, 1992). Likewise, interdepartmental cooperation affects technological viability (Souder, 1988). Two out of every three innovative firms report that interdepartmental cooperation is hampered, mainly due to a lack of mutual trust (Rochford & Rudelius, 1997). Departments should be involved from the onset. Along with well-defined tasks and responsibilities for all departments concerned, this creates cultural susceptibility to innovation. Adequate interdepartmental communication should be aimed for (Calantone et al., 1993). The term “adequate” should be read as flexible since formal and institutionalized communication is considered an impediment to success (Hopkins, 1981). A mission statement emphasizing the value of product development and internal entrepreneurship further adds to the firm’s cultural susceptibility (Johne & Snelson, 1988).

1 Openness of a firm's culture to R&D results is directly associated with commercial viability as well. Mansfield and Wagner (1975) argue that a culture susceptible to R&D-results improves the rate of successfully commercialized innovation projects by 15%.

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Experience with innovation Previous engagements in innovation projects are conducive to the firm’s technological capabilities as these improve skills decisive for the course of innovation projects. Firms should engage in projects that resemble the firm specific experiences with the technology, production and marketing skills involved2 (Stuart & Abetti, 1987; Bessant, 1993). In addition, projects resembling previous engagements allow for substantial reduction of the time-to-market (Wind & Mahajan, 1988). Experience enables the firm to capitalize upon learning-by-doing and learning-by-failing effects. Whereas the first improves the firm’s R&D efficiency, the latter exposes the firm’s weaknesses. Both phenomena are considered crucial in the product learning cycle (Maidique & Zirger, 1985; Zirger, 1997). Characteristics of the R&D team Several characteristics of the R&D team affect the firm’s technological capabilities. One is the team’s configuration; interdisciplinarity adds to the project's viability (Roure & Keeley, 1990). Although technological capabilities are indispensable, equilibrium between both technological and marketing skills should be aimed for: most often the emphasis is on the former (Cooper, 1983). A second distinctive feature is the attendance of a product champion. Confronting internal resistance to innovation, R&D teams supported by an individual acting as an innovation-dedicated internal entrepreneur are more successful than teams lacking this support (Link, 1987; Kleinschmidt & Cooper, 1995). In processing the firm’s internal and external scientific information, the product champion also acts as an efficient technological gatekeeper (Stuart & Abetti, 1987; Rothwell, 1992). Many projects lack the product champion’s devotion, mainly due to lack of top management support: only 40 percent of innovating firms deliberately encourage product champions to arise (Page, 1993). This is attributed to lacking familiarity with concepts to single out potential candidates (Wind & Mahajan, 1988). Two such concepts are psychological tests (Howell & Higgins, 1990) and adequate merit payments (Page, 1993). Rothwell (1992) opposes these concepts and argues that official nomination disrupts intrinsic motivation and dedication.

2 Experience is associated with commercial capabilities as well. Experience adds to the firm’s ability to understand customer needs, improving marketing skills (Maidique & Zirger, 1985).

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Firm strategy towards innovation An articulated innovation strategy is generally considered as a success factor. First, it provides a guideline for dealing with strategic issues, such as selecting the markets to enter and the skills to develop (Lester, 1998). Second, strategically planned projects enable the firm to take advantage of synergy between similar innovation projects. Third, learning-by-doing effects materialize, enabling the firm to reap benefits of previous successful innovations along with firm-specific skills that emanate from them (Rothwell, 1992). The relevance of innovation strategies has been evidenced by empirical studies; in order to maximize the benefits of previous innovations, innovation activities must be given a strategic direction (Cottam et al., 2001). Numerous innovation strategies are defined in the literature. Pro-active can be distinguished from re-active strategies. The first pursue product innovations in order to obtain product leadership in the market, whereas re-active strategies pursue product development as a safeguard against competing products (Johne & Snelson, 1988). One constitution of the pro-active strategies is the portfolio strategy, in which the firm simultaneously proceeds with several innovation projects in different phases of development (Gobeli & Brown, 1987). This strategy is generally considered appropriate. First, it preserves the firm from a short-term low risk profile. Second, portfolio planning induces projects targeted at specific, profitable market segments to be counter-balanced by projects based on fundamental R&D activities. Therefore, portfolio planning comes down to improvement as well as radical rejuvenation of the firm’s product line (Wind & Mahajan, 1988). Third, working on both incremental and radical innovations, this strategy allows for financing the latter with the bread-and-butter profits generated by the former. This preserves the firm from relying solely on product differentiation (Zirger, 1997). Fourth, portfolio planning adds directly to R&D skills: R&D teams involved in several projects simultaneously are more successful than those that are not (Kleinschmidt & Cooper, 1995). Although innovation strategies are conducive to the firm’s technological capabilities, these are not common practice; according to Page (1993), only half the innovating firms articulate an innovation strategy. Project related factors Two project related factors affect successful completion and hence contribute to the technological viability of an innovation project. These are the project’s complementarity with the firm’s resources and the management style.

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Complementarity The prospects of innovations depend on the project’s compatibility with the firm’s resources in broad terms, i.e. management and market research skills, sales, distribution, R&D and production facilities (Maidique & Zirger 1984; Stuart & Abetti 1987). Synergy emanates from phenomena like learning-by-doing and economies of scale and scope (Zirger 1997). Cooper (1983) and Link (1987) argue that synergy between R&D and marketing strengths is most important. Hopkins (1981) emphasizes synergy at the product level; the innovation must fit into the product group customers are already familiar with. Innovation management style Management style is often believed to affect project viability. According to Cozijnsen et al. (2000) adequate management of time, costs, information and decision-making determines 60% of the projects' viability. In order to make the project better manageable, most innovators split the project into constituent phases (see e.g. Crawford, 1991: 27). Most often, six phases are distinguished. The project is initiated by a planning phase, followed by phases of brainstorming, screening and evaluation, development and market research. It eventuates in the market launch phase. The more the process is kept to this trajectory, the more successful it will be (Cooper & Kleinschmidt, 1987). Factors crucial for success increasingly become manageable once the project is split up (Calantone et al., 1993): skipping phases is a main cause of failure (Wind & Wahajan, 1988). Empirical studies indeed show that technological viability increases with the extent to which the trajectory is completed (Kleinschmidt & Cooper, 1995). More important than completing the trajectory is the attentiveness with which it is pursued. Particularly in the cases of radical innovations this will reduce uncertainty (Rochford & Rudelius, 1997). In the literature, two phases of the trajectory are emphasized: planning and evaluation. During the planning phase, a medium-term plan identifying well-defined milestones should be formulated. Such a validation-driven planning converts uncertainties into clear tasks and responsibilities, thereby streamlining the course of the innovation project (Maidique & Zirger, 1985; Pinto & Slevin, 1989; Lester, 1998). The evaluation phase is emphasized because adequate evaluation enables the firm to distinguish viable projects from those less viable, thereby minimizing the project’s inherent uncertainty (Mansfield & Wagner, 1975).

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There are different views with regard to the relative impact of planning and evaluation during earlier and later phases of development. Cooper and Kleinschmidt (1987) argue that the early phases are most important. A detailed project definition in terms of market needs, market preferences and product specifications enables the innovator to arrive at a sound stop/go-decision. This contrasts with Schmidt’s view that the relevance of pre-development activities is exaggerated. Mistakes in the early phases are much less harmful than mistakes in the successive phases. “Upfront activities are important, but the later activities are critical” (Schmidt, 1995: 31). 2.2 Commercial viability With respect to the product’s commercial viability, two product (i.e. price and quality) and two market related factors (i.e. market concentration and market introduction) are generally acknowledged. Product related: Relative price and quality

Though recognized by only few studies, the relevance of a product’s price relative to competing products or substitutes remains undisputed. The extent to which the innovation reduces the customer’s total-costs-of-use (Cooper & Kleinschmidt, 1987) as well as the price in relation to quality is generally considered important (Madique & Zirger, 1984). It is generally acknowledged that successful innovations meet customer needs on a number of features simultaneously: quality, relative price, total-costs-of-use, convenience-of-use, after-sales services, and backward compatibility (Maidique & Zirger, 1984). Conversely, less successful innovations excel predominantly in a reduction of total-costs-of-use only (Roy & Riedel, 1997). The literature unanimously considers product quality a prerequisite for success (e.g. Link, 1987; Calantone et al., 1993; Hultink, 1998). Roure and Keeley (1990) consider it the only 'real' determinant of success. Market related: Concentration of targeted market and timing of market introduction One market related factor associated with the product’s commercial viability is the extent to which the product’s potential market is concentrated, reducing costs of communication. The relation may not be linear, though. Roure and Keeley (1990) report evidence of a U-shaped association between concentration of buyers and viability: high as well as low degrees of buyer concentration add to viability.

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Early market introduction may prove a competitive advantage (Hopkins, 1981; Maidique & Zirger, 1984). Johne and Snelson (1988) estimate that six to twelve months delay reduces financial returns by half. Therefore, it is recommended to create short-cuts in the innovation process to abbreviate the time-to-market. (Wind & Mahajan, 1988). Although the status of early market introduction remains undisputed, some qualifications have been made. First, the benefits of early introduction differ by type of innovation; whereas incremental innovations reap the benefits of accelerated introduction, original innovations do not. The latter gain from relatively extensive development trajectories in which the development process is pursued attentively (e.g. Yoon & Lilien, 1985). Second, early market introduction may be in conflict with the aim of product quality (e.g. Hultink, 1998). In spite of such arguments, many innovators respond to the need for speed. Among others, Page (1993) reports that over 40% of the innovators attempt to abbreviate the time-to-market.

3 Factors Lacking Consensus In our discussion on success factors that lack consensus in the literature, we again follow the classification in our above Figure 1 and distinguish between factors acting on technological (Sec. 3.1) and commercial viability (Sec. 3.2). 3.1 Technological viability Firm related factors With respect to the technological viability of an innovation project, there is no consensus on the relevance of two factors, i.e. organizational structure and R&D intensity. Organizational structure There is debate about the appropriateness of various organization structures for innovation activities. There is agreement that functional organizations are considered inadequate. Their pronounced levels of formalization and control are in conflict with the trial-and-error character of innovation processes (e.g. Johne & Snelson, 1988; Calantone et al., 1993). Innovators themselves tend to refute the functional structure as well; Larson and Gobeli (1988) report that only 20% of the functionally organized innovating firms is satisfied with this structure.

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The alternative, i.e. an organic, more flexible and adaptive structure, is unanimously preferred3. Organically organized firms outperform functionally organized firms in terms of success rates. Firms that explicitly strive for discovering and capitalizing on new market opportunities appear more often organically organized. Path analysis shows that organically organized firms develop superior technical and marketing capabilities; the latter two being recognized as important success factors autonomously (Calantone et al., 1993). In addition to these empirical observations, two theoretical arguments in favor of the organic structure dominate the literature. The first is sociological. Other than formal structures, which lead to selection and social confirmation, organic structures provoke individual expression and encourage product champions to arise. Considering the importance of the product champion’s attendance, the firm’s degree of “organicity” can be considered a success factor (Howell & Higgins, 1990). The second argument favoring organic structures stems from the nature of the innovation process. Equilibrium between formalization (in the interest of efficiency) and the advantages of a loose, open, creative and adaptive organic structure should be aimed for. Empirical studies show that successful innovative firms are loosely structured during the initiation phase of the development process and evolve to more formal structures as the product becomes better defined (Johne & Snelson, 1988; Rothwell, 1992; Bart, 1993). Arguments opposing organic structures have also been made. First, some empirical studies report a negative impact of organicity on a firm’s innovation capabilities. Among others, Rubenstein et al. (1976) argue that one ought to control the process tightly, especially during the early phases of the innovation process; the argument that autonomy acts as an incentive for innovation is false (see also Stuart & Abetti, 1987). Indeed, many successful innovators prefer tight control during the entire innovation process (Larson & Gobeli, 1988). Differences remain regarding two different constitutions of the organic structure: the venture team structure and the matrix structure (Johne & Snelson, 1988; Larson & Gobeli, 1988; Rothwell, 1992; Page, 1993; Kleinschmidt & Cooper, 1995; Lester, 1998). In both settings, a project manager is put in charge of a team composed of personnel from several functional areas within the firm. However, whereas the venture team does not involve the managers of the constituent functional areas, the matrix-structure does. The arguments in favor of the venture team relate to its autonomy. A venture team, behaving as a firm-within-the-firm, allows for an indispensable equilibrium between internal entrepreneurship and risks management. In addition, it allows for shorter 3 For a concise comparison between “functional” (or “mechanistic”) and ‘’organic’’ organization structures see the classical contribution by Burns and Stalker (1961: 119–122).

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decision making trajectories and improved flexibility (Lester, 1998). Many successful innovators have deliberately abandoned the matrix concept (Larson & Gobeli, 1988). However, the matrix-structure does have several advantages over the venture team. First, it imposes integration of various functional inputs. If interdisciplinarity is acknowledged as a success factor favoring creativity, the matrix structure outperforms the venture-team (Johne & Snelson, 1988). It also induces the firm to focus on both customer needs and technical feasibility during the entire innovation process (Rothwell, 1992). Second, empirical studies show that innovation projects embedded in a matrix structure obtain improved success rates (Kleinschmidt & Cooper, 1995). Hence the matrix structure became increasingly popular during the 1980s. During the 1960s, most innovation activities were conducted within autonomous development departments: In the early 1990s, three out of every four innovators have implemented some kind of matrix structure instead (Page, 1993). Most of these arguments are valid for both the venture team and the matrix structure. Only one argument is claimed to discriminate between both alternatives: relative to the venture team, the matrix structure allows for superior planning techniques (Larson & Gobeli, 1988). More generally, however, one should consider the impact of the organizational structure in perspective: “Organizations do not make R&D projects successful, individuals do” (Rubinstein et al. 1976: 18). R&D intensity Innovative output obviously increases with R&D investments. This is confirmed by empirical studies showing that substantial financial resources are a prerequisite for success (Page, 1993). Conversely, a lack of financial resources is considered a predominant factor of failure (Rubenstein et al., 1976). However, regarding R&D intensity (i.e. R&D expenditures relative to sales), this proposition is subject to debate. R&D intensive firms generally obtain improved (commercial) success rates (Gemunden et al., 1992); nonetheless, this relation is less than clear-cut. Among others, Acs and Audretsch (1991) argue that the causality between R&D input and innovative output is characterized by diminishing returns to scale. As far as large and complex organizations are concerned, this may be due to managerial diseconomies of scale. Brouwer et al. (1999) observe that the relation between R&D intensity and innovative output is moderated by such factors as regional knowledge spillovers, demand-pull effects or differences in technological opportunity. Such factors explain that R&D input and

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innovative output are far less strongly correlated than one would intuitively expect4. Cooper (1983) reports additional evidence. Firms spending only 1% of total sales on R&D generate one quarter of total sales with innovative products; firms spending at least 4% of total sales on R&D generate only 40% of total sales with innovative products. Project related factors Under this heading, only one factor remains ambiguous: top management support. Top management support empowers the innovation project and serves as a driving force for major initiatives and efforts. Rothwell (1992) emphasizes that top management support may be instrumental in overcoming internal resistance to innovation. Page (1993) concludes that one out of every four innovators qualify top management support as a prerequisite for success. Another argument relates to the concept of the product life cycle and claims that one can judge on the feasibility of an innovation project earliest five years after launch. Hence, innovation projects demand long-term commitment (Brenner, 1994). This requires a risk-tolerant top management that not only prevents viable projects to be aborted in advance, but also enables the firm to take advantage of learning-by-failing (Rothwell, 1992). Gobeli and Brown (1987) observe that top management support accounts for improved feasibility of radical innovations over incrementally improved products. Management support endangers the innovation as well. Excessive top management support may permit individuals to be involved for too long a period, causing stiffening (Rubenstein et al., 1976). Kleinschmidt and Cooper (1995) argue that top management support adds to failure as often as it does to success. 3.2 Commercial viability The literature remains inconclusive on four product and market related factors. The product related factors refer to the degree to which the product is innovative and technologically advanced. The market related factors concern the fierceness of competition and marketing capabilities.

4 For similar results see several chapters in Kleinknecht (1996) and Kleinknecht and Mohnen (2002).

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Innovativeness Arguments on innovativeness as a success factor are based on empirical observations. Some studies establish a U-shaped impact of innovativeness on viability. Among others, Kleinschmidt and Cooper (1991) observe that highly innovative products obtain success rates of 80%, whereas only half the innovations classified as medium-innovative prove viable; products characterized as moderately innovative show success rates of approximately 70%. Highly innovative products show improved success rates as these stand out in terms of product advantages. These innovations also benefit from relatively comprehensive pre-development activities. The modest success rates of medium-innovative products is ascribed to absence of synergy — technologically as well as from a marketing point of view. Exactly these synergy effects account for the viability of moderately innovative products. Hence one may argue that highly innovative products are not as risky as generally presumed (Kleinschmidt & Cooper, 1991). This proposition is in contradiction with research reported by Zirger (1997), suggesting linearity between innovativeness and viability with highly innovative products in the lead, followed by medium and moderately innovative products. Technologically advanced products The literature remains inconclusive as to whether the degree to which the product is technologically advanced affects its prospects. Several studies argue that this variable adds to viability (Cooper, 1983; Cooper & Kleinschmidt, 1987; Schmidt, 1995); others fail to establish any causality (Maidique & Zirger, 1984). Rackham (1988) reports a negative impact: an innovator’s emphasis on technical novelties may compromise commercial performance. In the cases of technologically advanced products, salesmen may focus on product features rather than customer needs. This discloses the essence of numerous superior but failed innovations; the feature-based approach tends to dominate the customer-based approach (Rackham, 1988). Competition Arguments on fierceness of competition as a success factor are based on empirical observations and remain inconsistent. Link (1987) considers fierce competition as a main factor of failure. Yoon and Lilien (1985) and Roure and Keeley (1990) argue that fierceness of competition is inversely related to new product success: The less competitive the market, the more viable the product. Stuart and Abetti (1987) establish

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similar causalities and suggest that innovators should penetrate less dynamic and less competitive (niche) markets. However, Cooper and Kleinschmidt (1987) and Kleinschmidt and Cooper (1995) argue that such market characteristics lack any predictive power for new product success, since fierceness of competition may be expected to be counterbalanced by entry or exit of potential and incumbent firms, respectively. More generally, this ambiguity resembles the long-standing discussion in industrial economics on the impact of market structure on innovation (see Kamien & Schwartz, 1982). Notably the survey by Scherer (1992) suggests that, if so, the impact of market structure on innovation cannot be overwhelmingly strong. Marketing Skills in market research are generally considered a success factor (Cooper, 1983; Yoon & Lilien, 1985; Calantone et al., 1993). Conversely, inadequate market research is considered the main factor of failure: over-estimated forecasts of demand and faulty translation of engineers’ desires into customers’ needs are well-known pitfalls (Hopkins, 1981). Although the literature is unambiguously supportive for adequate market research as a success factor, one prevailing instrument — involving consumers into the innovation process — remains controversial. One argument is the volatility of customer needs, which therefore require adequate study (Wind & Mahajan, 1988; Calantone et al., 1993; Asplund & Sandin, 1999). The majority of successful ideas originate within the market, not within the firm (Maidique & Zirger, 1984; Johne & Snelson, 1988). These arguments are empirically ascertained: three out of every four innovators value customer involvement; half the innovators consider it a prerequisite for success. Innovators involving customers attain significantly improved success rates (Gemunden et al., 1992). An argument opposing customer involvement is the pitfall of becoming prejudiced towards customer needs as the innovator involves customers on a more regular basis (Maidique & Zirger, 1984). Customer involvement may bias innovators towards imitative products, as customers express their preferences in terms of already familiar products. Customer involvement diminishes creativity and causes the firm to discard technology-driven ideas. Instead, equilibrium between technology-push and need-pull ideas should be aimed for (Johne & Snelson, 1988; Rackham, 1988).

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4 A Quantitative Assessment of the Literature

To examine factors of success and failure of innovations more systematically, we proceed with a meta-analysis of the literature reviewed above. We address two questions:

• To what extent are the studies on success and failure of innovation consistent in the importance ascribed to the various success factors?

• Is the consistency or inconsistency among these studies attributable to firm, project, product or market related factors?

As we aim at a factor ranking, not all forty-three studies discussed above can be included. The various contributions need to fulfill two criteria:

• The studies must have ranked the alleged success factors; and • The studies must have investigated a larger variety of factors. Inclusion of studies

investigating only a limited number of success factors would bias the analysis. Nine out of the forty-three studies reviewed above meet both criteria. The ranking of success factors by these nine studies is given in Appendix B. The appendix shows the ranking by importance, from 1 (= most important) to 21 (= least important). A zero value indicates that the factor was not considered or found insignificant. In order to obtain an impression of the (dis)-similarities among the nine studies, we test the null-hypothesis: “the ranking of factors is consistent”, using a non-parametric analysis of variance test (Kruskal-Wallis test). In a first round, we included all success factors exhibited in Appendix B and established significant dissimilarity5. Put differently, the ranking by importance of all success factors differs significantly between these nine studies. This relates to Montoya-Weiss and Calantone observing “a wide variation in results that are surprisingly non-convergent” (1994: 397). However, more detailed examination shows that this result is accounted for by the lower-ranking factors. Inclusion of the factors ranking from 1 to 10 only (i.e. excluding all lower- ranking factors) results in a highly insignificant test statistic6. This implies that consensus exists among the nine studies with regard to their ten most important success factors. 5 The Kruskal-Wallis test statistic is 58.8, exceeding the critical value (15.5) at n-1 (8) degrees of freedom and implying that the null-hypothesis cannot be accepted. 6 The Kruskal-Wallis test statistic is 5, not exceeding the critical value (15.5) at n-1 (8) degrees of freedom and implying that the null-hypothesis cannot be rejected.

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In order to identify factors that affect the ranking correlations, we divide the factors into groups, using the categories of the above Figure 1. First the factors are divided into two groups:

• Firm and project related factors (indicating technological viability); and • Product and market related factors (indicating commercial viability)

Results show significant ranking dissimilarity within both these groups, independently of whether only the first ten or all 21 ranks are included. We then subdivide the success factors into the four main categories detailed in the above Figure 1: (1) firm related; (2) project related; (3) product related; and (4) market related factors. We establish a significantly consistent ranking among the nine studies on firm and product related factors, while the rank correlation on project and market related factors is only weakly significant (at 10% level of significance). In interpreting these outcomes, one should bear the above qualitative literature review in mind. Here we observed that, among the project related factors, the degree to which a product is “innovative” and “technologically advanced” is quite differently appreciated among the studies reviewed. Similar ambiguity holds for the merits of top management support and, within the group of market related factors, fierceness of market competition and customer involvement. Such dissimilarity weakens the rank correlation within these groups. Within the groups of firm and product related factors, there is little ambiguity, the most important dissimilarities being related to the firm's organizational structure and R&D intensity. Different terminology complicates comparisons of our findings with the meta-analysis by Henard and Szymanski (2001). They argue, “Of the 24 predictors of new product performance investigated, product advantage, market potential, meeting customer needs, pre-development task proficiencies, and dedicated resources, on average, have the most significant impact on new product performance” (p. 362). In our view, a factor such as “market potential” is tautological, since the success of new products (whichever measure of success is used) will ultimately depend on successful market penetration. With some caution we conclude that our findings are not too distant from those of Henard and Szymanski. Our qualitative discussion allows us to be more specific. Henard and Szymanski argue that “product advantage” and “meeting customer needs” are positive factors throughout. We also concluded that “product quality and price relative to those of established products” are positive factors. For “customer involvement”, our results remain ambiguous. While customer involvement improves success rates, it may also bias innovation efforts towards incremental innovation. Henard and Szymanski’s emphasis on

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“pre-development task proficiencies” and “dedicated resources” relates closely to four factors that in our review were (predominantly) appreciated: a culture susceptible to innovation, experience with innovation, multidisciplinary R&D teams, and an articulated innovation strategy.

5 Conclusions In this paper we review the literature on determinants of successful innovation. We observe that the relevant studies are consistent in their ranking of their ten most important success factors, but remain ambiguous on less important success factors. Agreement exists on the positive impact of:

• A firm’s culture that is susceptible to innovation and recognizes the collective nature of innovation efforts;

• A firm’s experience with innovation projects (learning-by-doing; learning-by-failing);

• The multidisciplinary character of the R&D team; in particular equilibrium between technological and marketing skills, and the attendance of a product champion;

• An articulated innovation strategy and a management style suited to that; • Compatibility of the project with the firm’s core competences; • Product quality and price relative to those of substitutes; • Adequate timing of market introduction.

Agreement exists on a functional structure being in conflict with the trial-and-error character of the innovation process. An organic structure is unanimously preferred. Discussion remains as to whether the relatively autonomous venture team or matrix structure is preferable. In contrast to the 1950s and 1960s, in the 1980s the matrix structure is generally preferred since it better responds to the need for integration and control. Consensus exists on the relevance of marketing skills as many successful ideas originate in the market. Some contributors appreciate involving consumers in the innovation trajectory. Others argue that customer involvement may bias the innovation process towards imitative innovation, as customer preferences are articulated in terms of already familiar products. Obviously an innovating firm will need to aim for equilibrium between technology-push and need-pull innovations.

18

There is no conclusive evidence on top management support, R&D intensity and the degree to which a product is “innovative” and “technologically advanced”. This emphasizes the limitations of a one-sided “technology-push” approach. There is also ambiguity with respect to the fierceness of competition. These ambiguities parallel a longstanding and not quite conclusive discussion in the Industrial Organization literature on the relation between market structure and innovation (see the classical review by Kamien & Schwartz, 1982; or more recently by Scherer, 1992). Future research may examine success and failure of innovation using statistical databases that include, besides cross-sections, a time dimension. Distinguishing “easy” (incremental) from “heavy” innovations (changing strategic directions) may reveal the merits of factors such as consumer involvement, top management support, R&D intensity, market structure or innovativeness. Appendix A: Typology of studies reviewed in this paper (in chronological order)

Name Freeman et al. (1972 (SAPPHO)

Mansfield & Wagner (1975)

Rubinstein et al. (1976) Cooper (1980) (Project NewProd)

Sample 58 projects in scientific in-struments and chemicals (U.K.)

20 firms in chemistry and electronics (U.S.)

103 project in 6 firms (U.S.)

195 projects (Canada)

method empirical theoretical empirical empirical Subject Identification of factors

discriminating between success and failure

Impact of some organiza-tional aspects on suc-cessful innovation

Identification of factors of technological- and econo-mic success

Identification of factors of success and failure

Main results

Discriminating factors: • Understanding user

needs • R&D efficiency • External scientific

communication • Marketing

capabilities • Managerial capabili-

ties

• Early evaluation of commercial viability significantly im-proves viability

• Quantitative project selection is effective

• Susceptibility for R&D results is deci-sive

• Success is determi-ned by about 50 factors simultane-ously.

• There is no single magical success fac-tor.

Three factors determine half the viability: • Unique product feat-

ures and superiority • Market knowledge

and providence • Technological and

production synergy

19

Name Hopkins (1981) Cooper (1983) Johne (1984) Maidique & Zirger (1984)

(Stanford Innovation Project) Sample

101 firms (U.S.) 103 Canadian firms (New Prod-sample)

16 innovating U.K. firms in instrument industry

158 innovations in US electronics

method theoretical empirical empirical empirical Subject Identification of factors of

success and failure Importance of technolo-gical skills on viability

Experience as a guideline for the organizational as-pects of innovation activi-ties

Identification of factors of success and failure

Main results

Important factors: • Timing of market

introduction • Market research • Technological skills • Difficulties concern-

ing the orga-nizational structure, responsibilities and planning.

• Success rate is signi-ficantly higher than is generally assumed (56%)

• The relevance of success factors applies for all firms regardless of their unique characteristics

• Success is indepen-dent of financial R&D inputs

• Technological strengths are less important than mar-keting capabilities

• Firms with little or no experience with innovation benefit by separating initiation related tasks from implementation related tasks.

• A certain loosening of control and co-ordination is called for

Success factors: • Market knowledge • Customer interaction • Early market entry • Planning of the pro-

cess

Name Cooper (1985) Maidique & Zirger (1985)

Yoon & Lilien (1985) Link (1987)

Sample

195 innovation projects in 102 US firms

158 innovations in US electronics

112 innovations in 53 French firms

135 Austrian marketing managers

method empirical empirical empirical empirical Subject Design of a model for

project selection Identification of factors of success and failure

Comparison of incre-mental and radical innovations

Identification of factors of success and failure

Main results

Project selection serves as an instrument to improve viability. Eight properties determine viability. These can be employed to pre-dict the projects viability.

• All decisive factors are internal to the firm and are manage-able

• Innovators learn from failed projects.

• Both types of inno-vation differ in objective, marketing and timing of market introduction

Success factors: • Marketing and tech-

nological synergy • Quality • Customer needs • Price strategy • Distribution. Impact of success factors does not depend on the firm's innovation capabili-ties but on the degree to which a firm depends on innovations

20

Name Cooper & Kleinschmidt

(1987) Crawford (1987) Gobeli & Brown (1987) Stuart & Abetti (1987)

Sample

200 innovations in 125 US firms

No sample 13 US high-tech firms 24 new firms (U.S.)

method empirical theoretical empirical empirical Subject Measuring success and

identification of success factors

Evaluation of studies of success and failure

Comparison of different innovation strategies

Evaluation of perceived success factors

Main results

Success eventuates in: • Financial returns • Windows of oppor-

tunities • Market dominance The status of success factors depends on the measure of success employed.

Success/failure-studies re-main inconclusive. Further research is needed on: • Innovation strategies • Critical phases of the

innovation process • Impact of early mar-

ket introduction • Diffusion of innova-

tions

• 4 types of strategies are distinguishable

• Portfolio strategy is most appropriate for innovation

Negative causality between success and • Size / growth of

market • R&D intensity • Flexibility and adap-

tability of the firm's organizational struc-ture

Name Souder (1988) Wind & Mahajan (1988) Larson & Gobeli (1988) John & Snelson (1988) Sample

289 innovation projects (U.S.)

No clearly defined sample 540 innovation projects (U.S.)

no sample

method empirical theoretical empirical theoretical Subject Effects of hampered

R&D/Marketing-interface on project outcomes

Evaluation of develop-ment processes

Organizational setting of innovation projects

Identification of factors of success and failure

Main results

Degree of disharmony between marketing and R&D department is corre-lated to viability

• Viability remains short falling

• Guidelines for suc-cessful innovation

• Viability may be im-proved by orga-nizational adjust-ments, higher de-grees of innovative-ness and encouraging risk-taking attitudes

Matrix structure is most appropriate for innovation activities as far as cost, planning and tech-nological opportunities are concerned

The most common fac-tors of success and failure can be classified according to McKinsey's 7s-model

Name Pinto & Slevin (1989) Howell & Higgins (1990) Roure & Keeley (1990) Kleinschmidt & Cooper

(1991) Sample

159 R&D projects (U.S.) 50 firms (U.S.) 36 start-ups in US elec-tronics

195 innovations from 125 U.S. industrial firms

method empirical empirical empirical empirical Subject Identification of factors of

success and failure Impact of product cham-pion on viability

Importance of adequate reaction to time pressure and uncertainty

Causality between degree of innovation and success

Main results

Identification of 10 suc-cess factors. All vary in importance during the development process.

• Product champions add to susceptibility for innovation.

• Formally organized structures discourage product champions to arise.

11 measurable qualities of the firm determine re-sponsiveness to time pres-sure and uncertainty. These qualities determine the new ventures performance.

Relationship between success and degree of innovation is U-shaped.

21

Name Gemunden et al. (1992) Dougherty (1992) Rothwell (1992) Bessant (1993) Sample

848 U.S. manufacturing companies

no sample no sample no sample

Method empirical theoretical theoretical theoretical Subject Mobilization of external

resources and knowledge as a success factor

Investigation of differen-ces among the mental worlds of employees which keep firms from synthesizing their exper-tise

Evaluation of the inno-vation process

Effective management of technology: Which management capabilities are required and how to develop these?

Main results Three kinds of technology oriented external rela-tionships are important: • Customers • Research institutes • Other firms

For efficient innovation in large firms it is necessary to deal explicitly with the interpretative barriers to innovation.

The development process is evolving from techno-logy-pushed towards a system integrated network model

The prime management task is matching the tech-nology strategy pursued to the current and develop-ing capabilities within the firm

Name Griffin & Page (1993) Hart (1993) Bart (1993) Calantone et al. (1993) Sample

no sample 369 firms Undefined 142 US firms listed in the Fortune 500

method theoretical empirical empirical empirical Subject Examination of methods

employed to measure success

Examination of perfor-mance measures used in different studies

Importance of formal control procedures during the innovation process

Impact of organizational structure, marketing and technological skills on via-bility

Main results

Scientists measure success at the level of the firm. Innovators measure at the level of the product.

Instead of employing direct measures of success, one ought to employ indirect measures.

• Formal control pro-cedures ought to be minimized, but a mi-nimum level of con-trol remains ne-cessary

• Optimal level of for-mal control varies by project

Organizational structure determines marketing skills and hence viability

Name Page (1993) Schmidt (1995) Kleinschmidt & Cooper (1995)

Rochford & Rudelius (1997)

Sample 189 US firms two samples: 177 Canadian manufacturing firms obtained from Project NewProd and 142 Fortune-500 firms obtained from Spirit data set

103 innovation projects in 21 firms in chemicals (U.S., U.K., Canada, Germany)

79 US firms in medical instruments

method empirical empirical empirical empirical Subject Evaluation of projects Effect of proficiency of

innovation activities on level of success

Relative importance of perceived success factors

Relevance of completing development phases

Main results

• Half the innovators do not employ a stra-tegy towards inno-vation

• Success rates have not improved since 1980

• There remain oppor-tunities for improve-ment.

• Technological factors are more important than marketing fac-tors

• Product superiority is the most important success factor

• Perceived impact of factors differ from reality

• Development trajec-tory must be comple-ted attentively

• Marketing skills are more important than technological skills

Attentively completing all 13 phases of the deve-lopment process adds to viability

22

Name Zirger (1997) Roy & Riedel (1997) Lester (1998) Ekvall & Ryhammar

(1998) Sample 147 innovation projects in

US electronics 220 innovation projects in small and medium- sized UK firms

no sample 150 Swedish university managers

Method empirical empirical theoretical theoretical Subject Impact of experience with

innovation on viability Impact of degree of inno-vation and design on viability

Identification of success factors

Impact of leadership on organizational outcomes

Main results

Technological and market experience adds to viability

• Degree of innova-tion does not deter-mine viability

• Successful innova-tions are mostly de-signed with a multi-dimensional focus on quality, product features and design

Five decisive factors: • Top management

commitment • Culture susceptible

to innovation • Availability of con-

cepts and ideas • Organizational struc-

ture: venture teams • Project management

aimed at reduction of uncertainty

By affecting the social climate, the style of lea-dership affects organizational per-formance in terms of productivity

Name Rackham (1998) Asplund & Sandin

(1999) Brouwer et al. (1999)

Sample

3 products Swedish beer market 1989-1995

128 new product announ-cements published in trade journals

method Theoretical empirical empirical Subject Identifying factors of

failure of viable inno-vations

Survival rate of new products

Are urban agglomerations better breeding places for product innovation?

Main results

Viable innovations may fail due to the sales de-partment, which is product-oriented rather than customer-oriented

• Market uncertainty is a dominant factor

• Survival rates ap-pear to depend on volatile consumer preferences

Influential factors: • Continuity of R&D

effort • R&D intensity • Demand-pull • Firm size • Regional spillovers

23

Appendix B: Ranking of success factors by importance (0= not considered/insignificant; 1=most important)

Coop

er 1

980

Maid

ique

& Z

irger

19

85

Vos

s 198

5

Coop

er &

K

lein

schm

idt 1

987

Link

198

7

Stua

rt &

Abe

tti 1

987

Pint

o &

Sle

vin

1989

Calan

tone

&

Bene

detto

199

3

Kle

insc

hmid

t &

Coop

er 1

995

Firm's culture 0 0 2 0 0 0 0 0 0 Strategy towards innovation 0 3 0 0 0 0 0 0 0 Experience experience (in general terms) 0 2 0 0 0 2 0 0 0 experience/skills with

technology 0 0 0 8 0 0 4 1 12

experience/skills with marketing

0 0 0 7 0 0 0 2 0

R&D team R&D team (in general terms) 0 2 0 0 0 0 2 0 0 interdisciplinarity 0 0 0 0 0 0 0 0 13 attendance product champion 0 3 1 0 8 0 0 0 6 Organization organizational structure 0 0 0 0 0 0 0 4 0 'organicity' 0 0 0 0 0 4 0 0 0 autonomy R&D team 0 0 0 0 0 0 0 0 10 interdepartmental com-

munication 0 0 2 0 0 0 0 0 0

intradepartmental com-munication

0 0 2 0 0 0 0 0 0

embeddedness R&D team in firm

0 1 0 0 0 0 0 0 0

R&D expenses R&D intensity 0 0 0 0 0 3 0 0 0 availability financial resources 0 0 0 0 0 0 0 1 0 Innovation management innovation management (in

general terms) 10 0 1 2 9 0 0 0 9

completing development phases

0 0 0 0 0 0 0 1 0

planning/analysis 0 0 0 0 0 0 6 0 3 project definition 9 1 0 4 0 0 6 0 8 project selection 0 0 0 0 0 0 0 0 7 explicit responsibilities 0 0 0 0 0 0 0 0 10 process evaluation 0 0 0 0 0 0 5 0 0 Complementarity complementarity 5 0 0 2 0 2 0 0 0 marketing synergy 5 0 0 12 1 0 0 0 14 technological synergy 1 0 0 4 2 0 0 0 15 distribution synergy 0 0 0 0 0 0 0 0 19 production synergy 1 0 0 0 2 0 0 1 17 synergy core capabilities 0 1 0 0 0 0 0 0 10

24

Appendix II: Ranking of success factors by importance (continued)

Coop

er 1

980

Maid

ique

& Z

irger

19

85

Vos

s 198

5

Coop

er &

K

lein

schm

idt 1

987

Link

198

7

Stua

rt &

Abe

tti 1

987

Pint

o &

Sle

vin

1989

Calan

tone

&

Bene

detto

199

3

Kle

insc

hmid

t &

Coop

er 1

995

Top management support 0 1 0 0 0 0 5 0 0 Quality 0 0 0 3 3 0 0 3 1 Price price 0 1 0 11 5 0 0 0 0 price relative to quality 0 0 0 0 0 0 0 0 2 limited risk of purchase 0 0 0 0 0 0 0 0 20 Innovativeness innovativeness 0 3 0 0 0 0 0 0 0 unique / newness 3 0 0 6 0 0 0 0 0 Technological technologically advanced /

complexity 6 2 0 0 0 0 0 0 0

Product advantages / product superiority

3 0 0 5 4 0 0 0 4

meeting customer needs 4 1 0 9 0 0 0 0 5 ease of use 0 0 0 0 10 0 0 0 0 lower total-cost-of-use 0 0 0 11 4 0 0 0 0 Concentration 0 0 0 0 0 0 0 0 0 Timing market introduction 0 2 1 0 0 0 0 0 0 Market competition market competitiveness 4 0 0 0 0 0 0 0 18 market size 7 0 0 0 11 1 0 0 0 market growth 7 0 0 0 11 1 0 0 21 Marketing marketing (in general terms) 2 1 0 0 0 0 3 5 0 advertisement / promotion 8 1 0 0 10 0 0 0 0 adequacy of sales force /

distribution 0 1 0 10 6 0 0 0 16

forecasting turnover 2 1 0 0 7 0 0 0 0 market research 0 0 0 1 0 0 0 5 11 customer involvement 0 0 0 0 0 0 1 0 0 market definition 0 0 0 5 0 0 0 0 8

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